Generates plots to visualize and assess the performance of feature selection methods using supervised learning. It also provides functions to plot scree plots to visualize good cutting points for the number of features to be selected.
You can install the development version of EvaluateFeatureSelection like so:
install.packages("remotes")
remotes::install_github("Ahmad-Alsaleh/EvaluateFeatureSelection")Generate a scree plot
library(EvaluateFeatureSelection)
features_scores <- c(x1 = 0.8165005, x2 = -0.1178857, ...)
get_scree_plot(features_scores)
BAM Scores Scree Plot
Similarly, you can use get_auc_plot(...) or get_acc_plot(...) to
evaluate the performance of feature selection methods using supervised
learning and AUC/accuracy as the performance metric.
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